Showing posts sorted by relevance for query Stephen Baker. Sort by date Show all posts
Showing posts sorted by relevance for query Stephen Baker. Sort by date Show all posts

Sunday, February 25, 2018

The Numerati by Stephen Baker

Hari Seldon used mathematics to study psychology and society. He developed the science of psychohistory, which he would use to predict future social, economic and political trends. This was utter science fiction when I read Foundation in high school, and doubly so in the 1940s when Isaac Asimov was writing and publishing the stories that would eventually become the novel. (By the way, psychohistory now refers to the application of methods from psychoanalysis to the study of history and social sciences.)

We’ve come a long way. Computers are much more powerful and many of us carry a networked computer around in our pockets much of the day. The computers record a lot of information about us, especially how we use them, and are crunching the numbers so people can anticipate our wants and influence our behaviors.

Stephen Baker gives us a glimpse into that world in his book The Numerati. “Numerati” is Baker’s term for the mathematicians, computer scientists and other math-literate scientists and professionals who are trying to use numbers and equations to describe and predict human behavior.

This type of analysis has applications in many areas. As you might expect, stores, marketers and advertisers are using it to try to sell us stuff. Not only are they trying to persuade us, they are segmenting the market to try to get the highest prices they can for their products from each buyer (and spend less time dealing with die-hard bargain shoppers).

Similarly, politicians are using this type of analysis to reach swing voters. Companies are trying to get the most out of workers.  Health insurance companies are seeking to minimize exposures to risk. Law enforcement is getting all the information it can lay hands on to try to find the terrorist lurking in our midst (finding a needle in a haystack may be easier).

That sounds sinister, and Baker has reservations about the benefits of us sharing so much information, but there are opportunities for those of us who are not numerati, or can’t afford a staff of mathematicians to do our bidding. The numbers that show which workers are most productive could be turned around to help us show our value and potential win a raise or promotion. The numbers that show minute changes in our behavior might help us diagnose and treat diseases earlier and less expensively, or help us live more fully with chronic diseases. They might even match us with a soul mate.

Though science and technology have advanced in the decade since this book was published, the data sciences Baker described are still new. Some of the things we see being done with computers on television or film are still new concepts that don’t work nearly as quickly or accurately as depicted. However, people are working every day to make these technologies better.

If you’re interested in this book, you may also be interested in


Baker, Stephen. The Numerati. Boston: Houghton Mifflin, 2008.

Saturday, April 6, 2019

Naked Statistics by Charles Wheelan


Statistics provides of us with a power set of tools for describing things in our world and making inferences about them. They can also rely on math and logic that seems counterintuitive and they are subject to other pitfalls. Economist Charles Wheelan provides and accessible introduction into how we can use, misuse and abuse statistics in Naked Statistics.

Data is everywhere. In my life time, the falling prices and increased interconnectivity of computers have massively increased the collection of data. It can be overwhelming. At the same time, my experience as an engineer and government employee have left me frustrated with lack of data on some issue and wonder what inferences I might draw and how much I can rely on them.  Statistics provides us tools for dealing with these issues.

For instance, statistics provides us a way to summarize lots of data with a simple number such as an average (many people are familiar with sports statistics that summarize a performance of a play or team over a game, season or even a whole career). Statistics can help us find trends and estimate how much various factors may be contributing toward those trends. Even in the case where there is little data, statistics can help us evaluate the reliability of your conclusions (statistics can’t prove something definitively, but it can quantify how likely you are to be wrong).

“Statistics cannot prove anything with certainty.”-Charles Wheelan, Naked Statistics

Though he doesn’t delve too deeply into the mathematics of statistics, he shows that the math is often the easy part. Getting good data, designing experiments, constructing reasonable hypotheses, and avoiding bias present many stumbling blocks that can turn statistics into nonsense.

Not only that, people can take advantage of the weaknesses of statistics to provide persuasive support for wrong conclusions. Not everyone throwing around statistics intends to deceive, but a few do. A few just make mistakes, too. Wheelan describes many of the common mistakes people make while using statistics. This can help people new (or not new to statistics) avoid them. Possibly more important, it can help users of statistics recognize possible problems in how the statistics they use are developed or interpreted.

“Statistics cannot be any smarter than the people who use them.”-Charles Wheelan, Naked Statistics

This is not a statistics textbook. Wheelan does not delve into the details, but he does provide intuitive explanations of the concepts and simple examples. A student of statistics might find this book helpful in getting over some of the conceptual hurdles that may get in the way of understanding the rest of the material.

If you’re interested in this book, you may also be interested in

Wheelan, Charles. Naked Statistics: Stripping the Dread from Data. New York: W. W. Norton & Company, 2013.

Sunday, October 28, 2018

The Computers of Star Trek by Lois Gresh & Robert Weinberg


Star Trek fans, I’m one of them, have praised the show for the way it has anticipated technology. It used to be quite the thing to compare a flip phone to the Trek communicator.

However, have you ever watched a rerun of the show and seen something that now seems quaint, even ridiculous, especially when it comes to computers? Back in 1999, Lois Gresh and Robert Weinberg published observations like this, along with a few kudos for the shows, in The Computers of Star Trek.

The book covers episodes from the original series (TOS), The Next Generation (TNG), Deep Space Nine, Voyager and the films through Insurrection. While all the series, even the more recent prequel series Enterprise, depict a technologically advance future, none are focused on technology. They are more focused on telling stories that deal with the social issues in the periods in which they were made.

Gresh and Weinberg note this: Trek computers are mainly supersized versions of the computers of the time the show is made. In some ways, the Federation computers in the show are throwbacks to 1970s and earlier era mainframes, even though smaller, networked computers were becoming the dominant model when the revival series started in the late 1980s. This continued even as the Internet emerged and became part of the popular culture.

Of course the producers of the show aren’t especially interested in how computers actually work; they want to make an entertaining TV show and sometimes explore what is going on the society around them through the lens of a fictional future. Trek is interesting in this regard because it shows the attitudes of people about computers over time. In TOS computers are regarded with skepticism: computers break down, Spock is a hacker who takes over the ship, artificial intelligences take over planets but get fried by the illogic of emotions. By the time of TNG, computers are ubiquitous and acceptable—everyone uses them—but the threat of the Borg show concerns that computers might take over our lives and cause us to be depersonalized, destroying our individual identities.

An almost 20 year old book can’t help to be out of date, and the authors inevitably miss on some predictions. For instance, in their criticism of Trek’s take on medicine (not very advanced at all except when it is practically magic), the mention Army research into smart shirts that will monitor wearers for vital signs and injuries. It was a tee shirt with sewn in sensors that could be made for $30 (in 1998 dollars). Though we now have a lot of wearable technology, hospitals, soldiers and health nuts aren’t making use of cheap tees that keep track of their status moment by moment.

I don’t bring this up to knock the authors’ predictions. It’s hard to predict the future, especially by projecting from the current state of the art. Trek writers arguably haven’t tried very hard, but the show really isn’t about technology anyway.

If you’re interested in this book, you may also be interested in:

Gresh, Lois, & Robert Weinberg. The Computers of Star Trek. New York: Basic Books, 1999.

Saturday, September 29, 2018

450 Books Reviewed on Keenan's Book Reviews


I’ve posted reviews of 450 books on this blog. Here are links to the 50 most recent posts. Further down are links to more reviews.

First Time Reviews











Saturday, January 26, 2019

Learn Python 3 the Hard Way by Zed A. Saw


I’ve been putting some effort into learning to code in Python. One of the books I turned to is Learn Python 3 the Hard Way by Zed A. Shaw.

Shaw leads one through Python coding by providing an example of code in each chapter. You can enter it in your editor and run it. He then provides a set of exercises to break, test, modify or improve the code or come up with something on your own.

Actually, this isn’t a particularly hard way to learn coding. It takes time and effort to work through all the exercises in the book, but learning anything challenging and worthwhile takes time and effort. You’ll learn a lot about Python, what works and how to approach programming computers in general as you work through the book.

I don’t know that I have a good way of elaborating on a book like this. It is a workbook. You work through it slowly, step-by-step at the keyboard of your computer.

If you’re a beginner in programming, this is a good place to start. Python is reputed to be easy to learn, but is a powerful general-purpose language the you can use to do about anything you want. The early chapters and exercises are quite easy and Shaw builds skill upon skill as you proceed. In that sense, Shaw makes it easy, you just have to put in the work.

If you’re interested in this book, you may also be interested in:

Shaw, Zed A. Learn Python 3 the Hard Way: A Very Simple Introduction to the Terrifyingly Beautiful World of Computers and Code. Boston: Addison-Wesley, 2017.

Sunday, September 23, 2018

How Not to Be Wrong by Jordan Ellenberg


When people complain about math being too hard or impractical, one might expect a college math professor to take up a defense, which Jordan Ellenberg does in How Not to Be Wrong. He manages to make is his argument without resorting to equations, and with very few numbers.

Math is not all about equations and numbers (though these are important objects in math). Ordinary people do math frequently in the form of thinking with a little more depth, rigor and structure than usual. This is the power of math to help us make better decisions. Though Ellenberg covers a lot of ground in math, science and history, the notion of better decision making through math runs through each chapter.

Along the way, he debunks some common uses of math, even those that are prevalently used among math-minded scientists. For instance, he takes on the notion of statistical significance, which sometimes bothers me, too. Statistical significance by itself is not an arbiter of the truth of something. It has a lot more to do with a particular way of framing arguments and the sensitivity of an experiment. If you have a large enough sample, you’re likely to have statistically significant results, even if those results are insignificantly small. You can “prove” ridiculous, plainly wrong things using an argument from statistical significance because improbable things happen sometimes (actually a lot).

Ellenberg discusses the related subject of probability, which any book like this should. Human beings are pretty bad at grasping probability; it requires deeper, rigorous, structured thinking that sometimes runs counter to our intuition.

Though math is sometimes misused or misunderstood, Ellenberg is bullish on the power of math to help us make better decisions and understand the world more deeply. Math itself is a pretty deep world, and mathematicians have discovered connections between things that seem to be unrelated. That is part of the power of math. Solutions in one are often lead to applications in many others.

Of course, math won’t eliminate uncertainty, though it can help you understand uncertainties better. I’ve spent most of my career in and around government and Ellenberg expresses some empathy for decision makers in the realm of policy, writing, “Maker of public policy do not have the luxury of uncertainty that scientist do. They have to for their best guesses and make decisions on the basis thereof.” This guesswork can be done with humility and honesty, as is fitting in a republic.

While Ellenberg eschews the pile of symbols many people think of as math, he does not avoid deep, challenging questions. It’s not the math you’ll find in journals, but it’s not fluff. He doesn’t call people to join the ranks of academic mathematicians (though don’t give up on the idea just because it seems hard at first), but he argues that people in all manner of professions could benefit from education in math. If you’re interested in becoming such person, How Not to Be Wrong is a good introduction to how mathematicians think about the world.

If you’re interested in this book, you may also be interested in

Ellenberg, Jordan. How Not to Be Wrong: The Power of Mathematical Thinking. New York: Penguin, 2014.